ELK vs Graylog

Overview

ELK

Stacks863

Followers941

Votes23

Graylog

Stacks595

Followers711

Votes70

GitHub Stars7.9K

Forks1.1K

ELK vs Graylog: What are the differences?

Introduction: In the realm of log management and analytics, ELK (Elasticsearch, Logstash, and Kibana) and Graylog are two widely used platforms. Understanding the key differences between ELK and Graylog can help organizations make informed decisions when choosing a log management solution.

Data Collection: One key difference between ELK and Graylog lies in data collection. ELK utilizes Logstash for log ingestion, which makes it highly flexible for parsing and enriching data from various sources. On the other hand, Graylog has its data collection agent called Graylog Collector Sidecar, which simplifies the process of sending logs to Graylog.
Search Capabilities: Another crucial difference is in the search capabilities of ELK and Graylog. Elasticsearch, the core component of ELK, is known for its powerful and fast full-text search engine. This makes ELK particularly suitable for organizations dealing with complex search queries and large volumes of log data. Graylog, while also utilizing Elasticsearch, focuses more on structured data and offers a user-friendly search interface geared towards log analysis and monitoring.
Alerting and Dashboards: ELK and Graylog differ significantly in their approach to creating alerts and dashboards. ELK provides basic monitoring and alerting functionalities through features like Elasticsearch Watcher, which require additional setup and configuration. In contrast, Graylog offers a built-in alerting system and customizable dashboards out of the box, making it more user-friendly for users who prioritize ease of use.
Community Support: The level of community support is another differentiating factor between ELK and Graylog. ELK, being an open-source project with a large community of users and contributors, benefits from a wealth of community-created plugins, integrations, and resources. Graylog, while also open-source, has a slightly smaller community but offers professional support options for organizations requiring dedicated assistance.
Scalability and Performance: ELK and Graylog vary in their scalability and performance characteristics. ELK, particularly Elasticsearch, is known for its scalability and ability to handle massive data volumes efficiently. Organizations dealing with high-volume logs may find ELK more suitable due to its robust scalability features. Graylog, while scalable, may require additional configuration and optimizations to handle large-scale log data effectively.
User Interface: A notable difference between ELK and Graylog is in their user interface design and usability. Kibana, the visualization component of ELK, offers a more customizable and sophisticated user interface for creating visualizations and dashboards. Graylog, on the other hand, provides a simpler and more intuitive interface that caters to users looking for a straightforward log analysis experience without the need for extensive customization.

In Summary, understanding the key differences between ELK and Graylog in areas such as data collection, search capabilities, alerting and dashboards, community support, scalability and performance, and user interface can help organizations make informed decisions when selecting a log management platform.

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Detailed Comparison

ELK	Graylog
It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.	Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.
Statistics
GitHub Stars -	GitHub Stars 7.9K
GitHub Forks -	GitHub Forks 1.1K
Stacks 863	Stacks 595
Followers 941	Followers 711
Votes 23	Votes 70
Pros & Cons
Pros 14 Open source 4 Can run locally 3 Good for startups with monetary limitations 1 Easy to setup 1 External Network Goes Down You Aren't Without Logging Cons 5 Elastic Search is a resource hog 3 Logstash configuration is a pain 1 Bad for startups with personal limitations	Pros 19 Open source 13 Powerfull 8 Well documented 6 Alerts 5 User authentification Cons 1 Does not handle frozen indices at all
Integrations
No integrations available	GitHub

What are some alternatives to ELK, Graylog?

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

Sumo Logic

Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

LogDNA

The easiest log management system you will ever use! LogDNA is a cloud-based log management system that allows engineering and devops to aggregate all system and application logs into one efficient platform. Save, store, tail and search app

Related Comparisons

ELK vs Graylog: What are the differences?

Data Collection: One key difference between ELK and Graylog lies in data collection. ELK utilizes Logstash for log ingestion, which makes it highly flexible for parsing and enriching data from various sources. On the other hand, Graylog has its data collection agent called Graylog Collector Sidecar, which simplifies the process of sending logs to Graylog.
Search Capabilities: Another crucial difference is in the search capabilities of ELK and Graylog. Elasticsearch, the core component of ELK, is known for its powerful and fast full-text search engine. This makes ELK particularly suitable for organizations dealing with complex search queries and large volumes of log data. Graylog, while also utilizing Elasticsearch, focuses more on structured data and offers a user-friendly search interface geared towards log analysis and monitoring.
Alerting and Dashboards: ELK and Graylog differ significantly in their approach to creating alerts and dashboards. ELK provides basic monitoring and alerting functionalities through features like Elasticsearch Watcher, which require additional setup and configuration. In contrast, Graylog offers a built-in alerting system and customizable dashboards out of the box, making it more user-friendly for users who prioritize ease of use.
Community Support: The level of community support is another differentiating factor between ELK and Graylog. ELK, being an open-source project with a large community of users and contributors, benefits from a wealth of community-created plugins, integrations, and resources. Graylog, while also open-source, has a slightly smaller community but offers professional support options for organizations requiring dedicated assistance.
Scalability and Performance: ELK and Graylog vary in their scalability and performance characteristics. ELK, particularly Elasticsearch, is known for its scalability and ability to handle massive data volumes efficiently. Organizations dealing with high-volume logs may find ELK more suitable due to its robust scalability features. Graylog, while scalable, may require additional configuration and optimizations to handle large-scale log data effectively.
User Interface: A notable difference between ELK and Graylog is in their user interface design and usability. Kibana, the visualization component of ELK, offers a more customizable and sophisticated user interface for creating visualizations and dashboards. Graylog, on the other hand, provides a simpler and more intuitive interface that caters to users looking for a straightforward log analysis experience without the need for extensive customization.

ELK vs Graylog

Overview